11/05/2009

How can the diversification of transports can respond to changing long term urbanization ?

paper
contribu-ng
to
“Urban
Resilience
:
what
can
Urban
Governance
contribute
?”, superintended
by
Michaela
Hordijk,
Isa
Baud

Emmanuel
Raoult
(student
ID
:

6006108) 4320
words

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Introduction Last world reports about Global Warning are highlighting new issues about Green House Gas (GHG) : as efforts on industry pollution are satisfactory, the new major problem to address is the impressive growth of the GHG emissions due to transportation. Despite technological breakthroughs, the urban society based on car mobility is no more an option. As Tata is launching in India a very cheap micro car, we can expect enormous congestion and pollution in Indian cities. This environment approach is hiding other defaults of the car model : it reduces equal access, represents a huge investment for cities and citizens, threaten the cities dynamism because of the congestion. And finally, car is not The solution for transportation resilience, as we will show later. Therefore, we should look at transportationʼs diversity when thinking about resilience. Alternatives to car or not only mass transit systems, as almost all western countries planners think, but also rickshaws or buses. The main concept underlying this document is that we can link transportation resilience to transportation diversity and assess the resilience' strength by Land Use and Transportation Interaction (LUTI) models. This clearly focuses on long-term resilience and how urbanization shocks are absorbed by the city. Using these models, we will evaluate the transportation network in terms of long run unexpected shocks, which mean employment or residential major changes. To show this process, the first part links transportation resilience to diversity, the second part deals with forecasting models and indicators and finally the Bangalore case study will show how we can use this method and what is lacking to perform a resilience evaluation. This proposal doesnʼt deal with emergency response to new massive risks like floods, over heating weather... On the other hand, mass transit transport and other long-term solutions can address most of major problems linked to short term resilience. However, daily uncertainties like transportation accidents and other natural small unexpected events can do not fit in this study.

From transportation resilience to diversity This part will describe the first step of our thinking process : transportation resilience contains a main feature which is the diversity of transportation networks. What is transportation resilience ? The aim of this paper is to describe wether a transportation system in a city is resilient or not. We will talk now about urban transportation resilience. To define transportation resilience, letʼs use the previous paper “Transportation Resilience, planning land use and mobility management for unpredictable events”, part of the “Urban Resilience : what can Urban Governance contribute ?” work session. There, we mentioned Murray-Tuiteʼs (Murray-Tuite, 2006) definition of transportation resilience. This resilience could be described as the ability to withstand unpredictable events, reach a destination with an acceptable level of service, have a flexible system capable of learning from the past, benefit a safe and quick recovering network. But 3 other quoted terms should be highlighted for our study : autonomy, redundancy, diversity. Other terms like mobility, adaptability, safety, collaboration, improvising, evaluation (Online TDM Encyclopaedia, 2008) donʼt seem to be the core features of the long term transportation resilience, even if they certainly contribute. By ignoring the strength of a network or its safety we want to focus on urban planning issues : the security of bike or train transportation remains more on technical improvements than on city planning. However, the ability to operate separately, the redundancy and even more the diversity of networks rely entirely on planning decisions. As autonomy could be understood as an inherited feature of diversity and redundancy as diversity within the diversity, we will use Diversity to refer to these 3 concepts. As mentioned in the previous paper, transportation resilience could be 2/10

understood as the capacity to absorb a shock and to adapt. Again, the Diversity of a transportation network allows a better coping with unexpected events. This juxtaposition of nets absorbs more smoothly shocks. To illustrate that, we could use the example of an aerospace Composite (multiple layers) material do. Secondly, following this unexpected cases, Diversity allows a strong adaptation process : when a transportation network is not able to perform better, an other transportation network will provide an alternative in terms of capacity or availability. In the first definition of transportation resilience, adaptability is mentioned. It is not the same term we are talking about here : it is not a single transportation mean adaptability that we are talking about but the overall transportation network adaptability. Letʼs take a simple example : a city metropolitan authority decides to build a tramway line in one area called “happy neighborhood”. But this “happy neighborhood” - due to this tramway line ?... we could discuss that later - is turning into a massive, very dense residential area. The adaptation of the tramway system would be to build an other tramway line. The adaptation of the whole transportation system is to propose new buses services and a stronger use of bicycle to go to “lazy business district”, for example. Here one can understand the difference and the advantage of overall adaptation compared to a single transportation mean adaptation. Diversity then looks like an interesting field of study to understand transportation resilience concerning upcoming urbanization changes. As developing countries are experiencing fast changes in terms of urbanized areas, in particular slum transformation, it is even more interesting to focus on Diversity in India. Focusing on accessibility to address major issues As explained before, the Diversity of a transportation network leads to an auto-adaptive network concerning capacity, reliability or accessibility of a territory. This is even more important as urban form is changing more and more as Lefèvre says : “Proponents of the New Urbanism promoted an alternative with the concept of ʻdecentralized concentrationʼ.” (Lefèvre, 2009 : 941) Concerning these different centers : thanks to interconnections between different means of transport, a diversified transportation network can bring anybody to any point of a city territory. It can do that in a deeper and faster way than even cars : accessing city center using mass transit, accessing a special part of a building by bike... which are not “directly” possible by car. Even if depicting car as not efficient in terms of territory accessibility could be exaggerated, the equality of accessibility is really deeply improved when promoting a diversified transportation network. This clearly means that people not owning a car can absorb shocks such as unemployment or floods in their neighborhood when a diversified transportation system exists. Diversity ensure accessibility of services and city area for everybody but also avoid congestion : the multiple solutions to reach “lazy business district” from “happy neighborhood” or from the airport warrantee economic performance and, as mentioned in other papers on economic resilience, the city livability. Finally, we should notice that proposing diversified means of transportation can help to avoid buying a car and then, by extension, limit pollution and the environmental impact of transportation. We just reviewed here the 3 pillars of sustainability. Diversity is for us a basis for transportation resilience but could also been interpreted as a feature of sustainability. Then this resilience should be highly be linked to sustainability and these terms in this case are deeply interrelated. However, despite the fact that car is often a bad transportation response in urban areas, it is interesting to keep in mind that lower density areas could integrate the car system as a solution for a diversified transportation network. But car must be understood as a transportation mean and not as a private owned product, to ensure equality of access and use it for resilience purposes. 3/10

As explained before, long term transportation resilience is dealing with deep society changes, which include a shift in personal behaviors. After the second world war, people switch from bike to car, when entering modern consumer system. Nowadays, technology lead to more displacements, people are moving more and more for leisure activities (Bordeaux - Enquêtes Ménages, 1999). Diversity also let us have the capacity to adapt to this kind of change in a quite smooth way. We explained before how can Diversity almost define transportation resilience. The following text will now address main issues of diversification of transportation : governing and how can forecast tools help governing. Sundar, in a brief presentation points the main issues encountered in transportation in general :“Cities lack comprehensive mobility plans and lack of basic data, diffused institutional arrangements, adequate capacity” (Sundar, ? ). As Diversity clearly answers the capacity problem, we will focus on the two first themes and show that Diversity can give an answer to them.

Importance of governing Letʼs first explain the reasons that make governing institutions important. To propose a resilient transportation network using diversified means of transport, decision makers should enhance synergy between institutions in order to do avoid unnecessary overlapping transports in one area or a lack in transports in an other place. This transportation field is a cross theme, involving a large territory which corresponds to the cityʼs transport borders but not to the municipalityʼs most of the time. Local governments of large urban areas have then created specific transportation authorities to help synchronizing efforts linked to transportation. This will greatly help to create a real resilient territory. However, these authorities very often focus on how to build a metro line crossing different municipalities but donʼt have an integrated concept of transport interconnections or territory coverage. Having a common decision center about transportation for one city can also help saving money. More generally, optimizing public expenditures could be linked to enhance cooperation between the different components of the city. Bertolini emphasizes the case of decisions makers struggling with the civil society wills (Bertolini, 1999) and how finally local governments save money thanks to this strike. The need for a broader transportation authority is also linked to the question of transportsʼ diversity. As I will stress it later in this paper, Diversity includes personal vehicles like bicycles and they rely on peopleʼs will to use it. Therefore a comprehensive organization involving users is the answer. In order to implement a diversified network, authorities need to control as much as possible the density of the city so they can propose a maximized transport diversity solution. Controlling urban density could be seen as going against the theory of urbanization shocks which are supposed to test the transportation resilience. From a different approach, partially controlling Urban Sprawl helps smoothen any urban shock : it is fixing boundaries within which transportation networks can still adapt easily. This integrated control of urban sprawl also limits territory access inequities as local governments will not allow very far residential areas disconnected from employment areas. Lefèvre, when introducing his transportation case stud : the “lack of funds and institutions to orient the market dynamics.” (Lefèvre, 2009 : 941) is endangering Bangaloreʼs sustainability. But on the other hand he says that “there are many doubts on the feasibility of influencing these essentially behavioral drivers through public policies.” (Lefèvre, 2009: 941). This contrast tends to show that urban planners can influence the transportation resilience but some behavioral component are still a strong unpredictable part of the risks threatening the transportation networks.

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A common forecasting tool for resilience evaluation The importance of having an integrated approach of transportation, and its link to sustainability, which means resilience at one point, is explained by Birk and Zegras : “The worldwide use of the integrated transport planning approach will lead to a network of efficient, economically viable, environmentally sustainable cities.” (Birk & Zegras, 1994 : abstract). In order to propose tools to help decision makers and governing in general, we will propose here to focus on Land Use and Transports Interaction (LUTI) modeling. The first role of this model is to predict effects of a new transportation policy on land use and how a new land use can affect transportation networks (Deymier G., Nicolas J.-P., 2005). This paper will show that, by adapting the general transportation approach of these models, policy maker could use this tool to assess the transportationʼs diversity but also get some clues about the transportationʼs overall resilience. General overview First of all, urban planners need to get data so the LUTI model can understand the trends going on in the case study city. Letʼs take the UrbanSim LUTI model. It needs employment data, household data, parcel database, city general Plans, GIS basic overlays, some traffic analysis, travel model outputs but also development costs (OPUS UrbanSim Users Guide, 2009 : 16). Most of the time, employment and household data exist and GIS basic overlays too. The most difficult process is to gather information about how people are traveling (distance, vehicle, cost...). In France, highly comprehensive surveys are led almost every ten years, they are called “Enquête Ménages” (“household survey”) and contain a lot of data concerning transportation habits. It could be seen as a precious addition of data to the model. These LUTI models are working together with Transport Demand Management models such as “TransCAD” or “Davisum” for example. These last models generate traffic simulations through a 4 steps process : trip generation, trip distribution, mode choice and route assignment. When using LUTI models, urban planners can look at outputs as land use output or transportation output, in terms of traffic. Even if our approach is close to traffic issues, traffic is not an output which is interesting for us as is. We need then to adapt outputs to our question. Adapting to resilience evaluation We want to know if a city has a transportation system which is diversified enough to be resilient. This could be summarized by 2 results : how many transportation solutions do we have nearby and the rate of used capacity on maximum capacity of each transportation mean. The first data is not really concerning forecasting but more gathering information about different transportation means in the area. The second is using the traffic output of LUTI model synchronized with a Transport Demand Management software. To visualize this forecasted Diversity, we can imagine to give a different thickness according to maximum capacity and different colors showing the forecasted congestion level of every transportation segment. Finally, by using grey levels to illustrate the projected density, we can then analyze how resilient a neighborhood is.

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figure 1 : simplified diversity customized view from LUTI output

We can also imagine an evaluation of the number of different routes possible from one residential area to main activity areas. These explanation tends to show that we can measure transportation resilience. However, we should still think about how to create a synthetic index of resilience as the above illustration need a map and expert analysis to assess resilience. Scenario In order to test this resilience, we need to test different scenarios. This is also how planners use LUTI modeling. And Jonsson repeated it in his article about sustainability and land use - transport modeling : “Making long term forecasts is inherently riddled with uncertainties, so it is dangerous to view these results as what will happen. A much more productive way of looking at them is as internally consistent scenarios of the future.”(Jonsson, 2008 : 40). When talking about resilience, this approach is even more relevant : there is no resilience optimum but more a bunch of scenarios which could show some resilient features. We can find the same kind of contrast in the aerospace industry : determine what is the best shape for a turbojet engine blade is not really possible. Engineers are building then scenarios to evaluate which shape could be really interesting. The input is not the optimal shape parameters (which is already really difficult to determine) but the shape on itself and which quantified advantages can we get from this shape. By using scenarios, which for us make sense and are showing some possible changes, we can evaluate and compare them to tell wether one policy implementation or an other will influence the transportation resilience, which means here Diversity. Limitations However, some processes can not be caught using this model. For example, we are trying to draw some scenarios and then evaluate if the transportation system will be resilient. But then, this process is inherently the contrary of unexpected changes or events. This could be seen as a nonsense because we are focusing on major shocks. However, even if we can not predict the specifications of a shock, scenarios still help us to evaluate the cityʼs resilient. For example, one can propose a kind of benchmark by applying 4 scenarios to each city and then compute an overall transportation resilience index. When not looking at the theoretical issues, we should remind the reader that this kind of software needs a lot of data and, in a second time, calibration. It needs urban planner expertise but also software engineers, modeling experts, economy and transports specialists. To sum up, it is a heavy process but it could worth it as a decision making major tool. LUTI models seem to be relevant as soon as decision makers can hire a large panel of experts to make these models work in the targeted metropolitan area. The share 6/10

of community experience is also a major point. This is what Batty and Torrens say : “Where we are dealing with systems that are intrinsically uncertain and infinitely complex, then the only way forward is to learn the limits to such systems and in this way, to fashion our models to account for such limits.” (Batty, Torrens, 2005 : 765). This quote could be the conclusion in a nutshell of this part : we have complex systems and uncertainty but by knowing the model limits we can make it an important and relevant decision making tool.

Case study We will focus here on the case of Bangalore. Lefèvre performed a multi scenario LUTI evaluation of the city of Bangalore (Lefèvre, 2009). After explaining what Lefèvre did, we will suggest components that could help the transportation resilience evaluation. Context India has a very fast growing urban population. It also implies a huge travel demand growth. In the same time, decision makers are neglecting non-motorized transportation, donʼt implement any integrated land-use and transportation policy. Inadequate public transportation and fast rising population incomes, especially in Bangalore, are leading to challenging issues and are increasing the risk threatening Bangaloreʼs dynamic. Bangalore was so called “garden city”, and Heitzman said that it was probably one of the main reason why the city grew so fast (Heitzman, 2004). Now urbanization is endangering these amenities. And Lefèvre reminds us that “Technology improvement [...] will not be the hoped-for ʻsilver bulletʼ, especially for poor and fast-growing cities.” (Lefèvre, 2009 : 940). This means that modernism will not solve the urbanization issue. This growing urban sprawl spreading bangalore inhabitant on a larger and larger territory is catalyzing the “exacerbation of social inequalities” (Lefèvre, 2009 : 942). In the same time, Lefèvre noticed that this precise urban sprawl could be understood as an unexpected outcome of the development of the city : “The passage from urban growth in concentric circles [as Von Thunen model forecasted it], which produced the dense fabric of the earlier city, to this linear and divergent expansion, has led to an imbalance between the different zones of the urban area.” (Lefèvre, 2009 : 942). This is precisely what transportation resilience is supposed to address. Urbanization is not a linear process and contains risks of shocks in terms of real estate and employment, wether they are spatial or time shocks. However, and this would be also a concluding remark, transportation resilience can not be linked only to transportation features and should be linked then to land-use policies. Study goals and method The transport authority of Bangalore wanted to reduce congestion and increase road safety. From this context, the author performed a 3 scenarios LUTI simulation, using the Tranus program, an other LUTI model software. These scenarios are “business as usual” , which means no major changes in the city planning decisions, “Metro”, which proposes to detect what kind of changes would occur with a new metro network, and finally the “Metro Plus” scenario which consists in building subway lines synchronized with a strong land use policy. To model so, he “defined two modes of transportation (public and private) and five operators (bus, rickshaw, car, motorcycle, walking)” (Lefèvre, 2009 : 946). What can be noticed here is that the author mentioned rickshaws which are quite particular to Asia and India in particular.

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figure 2 : Projected evolution of land consumption, from Lefèvre 2009

Lefèvre concludes that “[...] these results demonstrate the relevance of focusing the urban governance of transportation energy planning on the interactions between transport system and land uses system”. Beyond the “transportation energy planning” that the author is focusing on, we notice the importance of LUT Interactions in the transportation process, in particular for transportation resilience. However, we should point the fact that this article is only dealing with subway scenarios and completely ignore other transportation means improvements, like bus or bike lanes. These other vehicles could also be linked to community and individual actions which could largely influence the cityʼs transportation landscape, as mentioned by Keenan Steiner on a blog about rethinking Indiaʼs development (CSTEP blog, 3/2009). The next step in forecasting would be then to better integrate rickshaws, walking or buses strategies in order to assess the Diversityʼs real influence. Sudarsanam Padam & Sanjay Kumar Singh in their article show how important it could be to integrate different means of transportation, especially enhanced bus services (Sudarsanam Padam & Sanjay Kumar Singh, 2004).

Conclusion This article first rewind to the precedent contribution of this course about transportation resilience. By reusing this definition we focus on Diversity of transportation as a highly effective transportation resilience agent. This analyze drove us to the sustainability issues 8/10

and show how transportation resilience is hitting each 3 pillars of sustainability. Diversity is really highlighting and strengthening this hidden part of resilience. In the second part, we looked at the LUTI models that are proposed to assess the effect of different planning levers on land use and transportation evolutions for the coming 20 years. We then propose an adaptation of the standard output to evaluate the transportation resilience of an urban area, according to its transportation Diversity. Finally, the overview of the Bangalore case show what kind of outputs are now proposed and we point what should be done to include Diversity of transportation in a better way. From both the general LUTI overview and the case study, we should draw two main concepts to be developed : first, it would be interesting to enrich the LUTI model by general observations and surveys about how Diversity of transportation, density and landuse interact. Following this guideline, we should think about how land-use, and not only Diversity, affects the transportation resilience. On the other hand, there is clearly a lack in LUTI models on how bicycle or buses or similar vehicles can influence the overall simulation. LUTI models have focused mainly on Metro and car issues. As bicycle policies and sustainable issues are becoming more and more important now, and as far as we know that subway-only solutions will not solve urban transportation issues, we should think about implementing new behaviors models linked to these ignored transportation means. From a less technical point of view, we should remember that this kind of really concrete result is helping decision makers to precisely make a decision : the proposed method clearly draw a path toward the evaluation of transport resilience. These tools also fit well to public communication and explanation. LUTI Simulations could be used of course as a material for community mobilization and deliberation on one project.

Bibliography (in order of appearance) 1 :Pamela M. Murray-Tuite, 2006, “A COMPARISON OF TRANSPORTATION NETWORK RESILIENCE UNDER SIMULATED SYSTEM OPTIMUM AND USER EQUILIBRIUM CONDITIONS”, page 1398, Abstract paragraph one line 2 : Victoria transport policy institute, 7/2008, Online TDM Encyclopaedia, “Evaluating Transportation Resilience; Evaluating the Transportation Systemʼs Ability to Accommodate Diverse, Variable and Unexpected Demands with Minimal Risk”. Available at: http:// www.vtpi.org/tdm/tdm88.htm [Accessed 23 March 2009] 3 : Lefèvre, 2009, “Long-term energy consumptions of urban transportation: A prospective simulation of ʻʻtransport–land usesʼʼ policies in Bangalore$”, Energy Policy 37 (2009) 940– 953 4 : aʼurba, 2001, “Enquête Ménage de 1999, éléments dʼanalyse” 5 : Sundar, “sustainable mobility - challenges for urban India” 6 : Bertolini, 2005, “Evolutionary urban transportation planning: an exploration”, Environment and Planning A 2007, volume 39, pages 1998 ^ 2019 7 : Zegras, P C; Birk, M L, 1994, “MOVING TOWARD INTEGRATED TRANSPORT PLANNING: ENERGY, ENVIRONMENT, AND MOBILITY IN FOUR ASIAN CITIES”, Transportation Research Record, Issue Number: 1441, Publisher: Transportation Research Board, p. 84-92 8 : Deymier Ghislaine, Nicolas Jean-Pierre, “Modèles d'interaction entre transport et urbanisme : état de l'art et choix du modèle pour le projet SimBad”,07/2005 9 : OPUS UrbanSim Users Guide “The Open Platform for Urban Simulation and UrbanSim, Version 4.2.2 : Users Guide and Reference Manual”, Center for Urban Simulation and Policy Analysis, University of Washington, 02/2009, URL : http:// www.urbansim.org/opus/releases/latest-stable-release/docs/opus-userguide.pdf

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10 : R. Daniel Jonsson, 2008, “Analysing sustainability in a land-use and transport system” , Journal of Transport Geography 16 (2008) 28–41 11: Michael Batty, Paul M. Torrens, 2005, “Modelling and prediction in a complex world”, Future 37 12: Heitzman, J., 2004, “Network City: Planning the Information Society in Bangalore”. Oxford University Press, Oxford. 13 : Keenan Steiner , Improving Bangaloreʼs transport system, 3/2009, CSTEP blog : http://blog.cstep.in/?p=10 14 : Sudarsanam Padam, Sanjay Kumar Singh ; “Urbanization and urban transport in india: the search for a policy”, 2004, European Transport \ Trasporti Europei n. 27 (2004): 26-44

Internet Resources Bangalore Metropolitan Transport Corporation : http://www.bmtcinfo.com/english/index.htm Bangalore Metropolitan Land Transport Authority : http://www.bmlta.org/BMLTA Interesting daily resilience map : http://map.bmlta.org/map.html http://www.karnataka.gov.in/urbandevelopment/index.html Karnatakaʼs Urban Development department http://urbanindia.nic.in/moud/programme/ut/main.htm Ministry of urban development, Urban transport heading

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